Statistical distribution

Statistical Distribution

A statistical distribution is a representation of the frequencies of potential outcomes or the probabilities of different outcomes in an experiment or survey. It is an essential concept in statistics, probability theory, and related fields.

Overview

A statistical distribution describes the likelihood of an outcome in an experiment or survey. It can be represented in various ways, such as a table, graph, mathematical formula, or set of percentiles. The distribution can be either discrete or continuous, depending on whether the data can take on any value or only certain specific values.

Types of Statistical Distributions

There are numerous types of statistical distributions, each with its unique properties and uses. Some of the most common include:

• Normal Distribution: Also known as the Gaussian distribution, it is a continuous distribution that describes data that clusters around a mean or average. It is the most common distribution in statistics.

• Binomial Distribution: This is a discrete distribution that describes the number of successes in a fixed number of independent Bernoulli trials with the same probability of success.

• Poisson Distribution: This is a discrete distribution that expresses the probability of a given number of events occurring in a fixed interval of time or space.

• Exponential Distribution: This is a continuous distribution that describes the time between events in a Poisson point process.

Applications

Statistical distributions are used in a wide range of fields, including mathematics, physics, engineering, computer science, economics, and social sciences. They are used to model real-world phenomena, make predictions, and test hypotheses.

See Also

• Probability Theory
• Descriptive Statistics
• Inferential Statistics
• Statistical Model